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Gemini 2.0 Flash vs Gemini 2.0 Flash Thinking

Gemini 2.0 Flash and Gemini 2.0 Flash Thinking are closely matched at 16.5 and 16.7 on the LLM Stats Score.

Google · Google · Updated for 2026

Which is better?

Gemini 2.0 Flash and Gemini 2.0 Flash Thinking are closely matched on the overall LLM Stats Score at 16.5 and 16.7.

In the 2 individual benchmarks reported for both models, Gemini 2.0 Flash Thinking wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 2.0 Flash

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose Gemini 2.0 Flash Thinking

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Jan 2025

At a glance

The differences that matter most.

Gemini 2.0 Flash
Google
Gemini 2.0 Flash Thinking
Google
Core performance indexes
LLM Stats Score
16.5
#221
16.7
#219
Reasoning
15.8
#220
17.0
#212
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
1,048,576
—

Individual benchmarks

13 reported for Gemini 2.0 Flash · 3 for Gemini 2.0 Flash Thinking

2 shared

Gemini 2.0 Flash outperforms in 0 benchmarks, while Gemini 2.0 Flash Thinking is better at 2 benchmarks (GPQA, MMMU).

Gemini 2.0 Flash Thinking significantly outperforms across most benchmarks.

Thu Sep 17 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Gemini 2.0 Flash specifies input context (1,048,576 tokens). Only Gemini 2.0 Flash specifies output context (8,192 tokens).

Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Thu Sep 17 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 2.0 Flash and Gemini 2.0 Flash Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 2.0 Flash

Text
Images
Audio
Video

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 2.0 Flash

Proprietary

Closed source

Gemini 2.0 Flash Thinking

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 2.0 Flash was released on 2024-12-01, while Gemini 2.0 Flash Thinking was released on 2025-01-21.

Gemini 2.0 Flash Thinking is 2 months newer than Gemini 2.0 Flash.

Gemini 2.0 Flash

Dec 1, 2024

1.8 years ago

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.7 years ago

1mo newer

Knowledge Cutoff

When training data ends

Both models have the same knowledge cutoff date of 2024-08-01.

They should have similar awareness of historical events and information up to this date.

Gemini 2.0 Flash

Aug 2024

Gemini 2.0 Flash Thinking

Aug 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash and Gemini 2.0 Flash Thinking side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash
✓ Preferred
Gemini 2.0 Flash Thinking
Open in Playground

FAQ

Common questions about Gemini 2.0 Flash vs Gemini 2.0 Flash Thinking.

Which is better, Gemini 2.0 Flash or Gemini 2.0 Flash Thinking?

Gemini 2.0 Flash and Gemini 2.0 Flash Thinking are closely matched on the LLM Stats Score at 16.5 and 16.7. Gemini 2.0 Flash is made by Google and Gemini 2.0 Flash Thinking is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.0 Flash compare to Gemini 2.0 Flash Thinking in benchmarks?

Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%. Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%.

What are the context window sizes for Gemini 2.0 Flash and Gemini 2.0 Flash Thinking?

Gemini 2.0 Flash supports 1.0M tokens and Gemini 2.0 Flash Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 2.0 Flash and Gemini 2.0 Flash Thinking?

Key differences include LLM Stats Score (16.5 vs 16.7). See the full comparison above for benchmark-by-benchmark results.

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